Microelectromechanical systems (MEMS) have the potential to transform a number of different industries in modern society. Ranging from aerospace to bioengineering, the impact of MEMS is likely to be as profound and pervasive as that of integrated circuits. In particular, the use of MEMS devices as sensors and actuators in electromechanical systems is very promising. By creating electrical and mechanical components on a silicon substrate using standard microfabrication techniques, MEMS technology enables relatively small, cheap, and accurate sensing devices to be created. MEMS sensors and actuators are already being used in numerous commercial devices, including automobile airbag accelerometers and vibration sensors.
A common application of MEMS sensors has also been in the use of gyroscopes, which may use the motion of a vibrating element to measure an angular rate of rotation. A variety of MEMS gyroscopes are commercially available, including tuning fork gyroscopes and angular rate sensing gyroscopes. In the case of tuning fork gyroscopes, three orthogonal axes (drive, input, and sense) may be utilized to describe gyroscope motion. When a tuning fork gyroscope is in operation, a vibrating element may be placed in oscillatory motion along the direction of the drive axis while the gyroscope rotates about the input axis. These motions may result in a Coriolis acceleration that can be measured along the direction of the sense axis. Using a well-known mathematical relationship, the angular rate of rotation of the gyroscope about the input axis may then be calculated.
Despite the advantages of MEMS technology, prior art MEMS sensors often face a number of drawbacks. MEMS sensors may have performance characteristics such as voltage outputs that are sensitive to temperature changes. To reduce this sensitivity, a prior art MEMS sensor is often tested in a thermal chamber to measure its output at a variety of different temperatures. Complicated regression analysis (e.g., using cubic or fifth order functions) may then be utilized to map the thermal sensitivity of the MEMS sensor. The coefficients obtained from the regression analysis may subsequently be stored within a microprocessor and provided to the MEMS sensor while in operation to compensate for temperature changes. Thus, a number of complicated components may be required for reducing the thermal sensitivity of a prior art MEMS sensor.
Accordingly, it is desirable to have a MEMS sensor that overcomes the above deficiencies associated with the prior art. This may be achieved by utilizing a passive temperature compensation technique for improved performance of a MEMS sensor.